Publications

On tighter estimation of the time derivative of Lyapunov-Krasovskii functionals and stability criteria for time-delay systems

This paper is concerned with stability of a linear system with a time-varying delay. The direct Lyapunov method is a powerful tool for studying stability of the system. Note that a tighter estimation on the time derivative of some Lyapunov-Krasovskii functional usually leads to a less conservative stability criterion. First, by introducing an auxiliary vector-valued function, this paper proposes a novel integral inequality, which can provide a tighter estimation on the integral term appearing in the time derivative of the Lyapunov-Krasovskii functional. Second, by introducing an augmented Lyapunov-Krasovskii functional, this novel integral inequality is employed to derive a stability criterion for the system with a time-varying delay. Finally, it is shown through a well-studied numerical example that the proposed stability criterion outperforms those using the IQC approach, the quadratic separation approach, the Wirtinger-based integral inequality approach and the free-matrix-based integral inequality approach.

How often should one update control and estimation: review of networked triggering techniques

Management of resources is a constant topic in industrial systems. How to use minimum communication resources is of particular interest for control and est

Controller Design for Networked Fuzzy Systems

This paper deals with the problem of network-based controller design for the given T-S fuzzy model. The effects of both network-induced delays which are assumed to be interval time-varying, and data packet dropout will be investigated. Based on an integral inequality and a matrix inequality, a delay-dependent sufficient condition for the existence of a network-based controller is formulated in terms of a linear matrix inequality by adjusting two parameter matrices. And no model transformation is employed. Moreover, in order to obtain a less conservative design method of the network-based controller by solving the obtained nonlinear matrix inequalities and to avoid adjusting any parameter matrix, a novel iterative algorithm is proposed. An illustrative numerical example is also given to show the effectiveness of the proposed design method.

Design of controller possessing integrity for uncertain continuous-time systems

This paper is concerned with the synthesis of a state feedback control system which possesses both integrity and robustness. A state feedback control law which retains asymptotic stability against arbitrary actuator failure and parameter perturbations is derived using a positive definite symmetric solution of a new Riccati-type matrix equation. Moreover, a design procedure is proposed, and the effectiveness of the procedure is demonstrated with a numerical example and simulations results.

Optimal Guaranteed Cost Control of Linear Uncertain Systems with Input Constraints

Optimal Chiller Loading Based on Collaborative Neurodynamic Optimization

Chillers are indispensable machines for heat removal and the primary sources of power consumption in heating, ventilation, and air conditioning systems. In this paper, a cardinality-constrained global optimization problem is formulated to minimize power consumption for optimal chiller loading. The formulated problem is solved using a collaborative neurodynamic optimization method based on multiple neurodynamic models. Experimental results based on available actual chiller parameters are elaborated to demonstrate the superiority of the proposed approach to many baseline methods for optimal chiller loading.

Extended state-based finite-time fuzzy optimal recoil control for nonlinear drilling riser systems after emergency disconnection

To guarantee the safety and reliability of drilling riser after emergency disconnection, it is significant to investigate and refrain recoil response of the riser. This paper deals with the problem of Takagi–Sugeno (T-S) fuzzy recoil dynamic modeling and optimal recoil control of nonlinear deepwater drilling riser systems subject to friction resistance of fluid discharge and platform heave motion. First, a nonlinear recoil control model of coupled riser-tensioner is proposed by taking the nonlinear top tension of tensioner into account. Then, a T-S fuzzy dynamic model of the riser-tensioner system is established to approximate the original nonlinear one by using fuzzy modeling scheme. Third, an augmented T-S fuzzy model of riser system is proposed, where the linear exosystem model of friction resistance and platform heave motion is utilized. Fourth, a finite-time fuzzy optimal recoil controller is designed to suppress the recoil response of the riser, the existence and design algorithm of the fuzzy optimal recoil controller are derived. Simulation results demonstrate that the nonlinear recoil model is more accurate than the existing linear one to describe the recoil characteristics of the riser, and the fuzzy optimal recoil controllers are effective to reduce recoil responses and guarantee the safety of the riser significantly.

A Recursive Approach to Quantized ${H_{\infty}}$ State Estimation for Genetic Regulatory Networks Under Stochastic Communication Protocols

This paper deals with the finite-horizon quantized H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> state estimation problem for a class of discrete timevarying genetic regulatory networks with quantization effects under stochastic communication protocols (SCPs). To better reflect the data-driven flavor of today's biological research, the network measurements (typically gigabytes in size by highthroughput sequencing technologies) are transmitted to a remote state estimator via two independent communication networks of limited bandwidths. To lighten the communication loads and avoid undesired data collisions, the measurement outputs are quantized and then transmitted under two SCPs introduced to schedule the large-scale data transmissions. The purpose of this paper is to design a time-varying state estimator such that the error dynamics of the state estimation satisfies a prescribed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance requirement over a finite horizon in the presence of nonlinearities, quantization effects, and SCPs. By utilizing the completing-the-square technique, sufficient conditions are derived to ensure the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> estimation performance and the parameters of the state estimator are designed by solving coupled backward recursive Riccati difference equations. A numerical example is given to illustrate the effectiveness of the design scheme of the proposed state estimator.

Robust stability for a class of linear systems with time-varying delay and nonlinear perturbations

The robust stability of uncertain linear systems with a single time-varying delay is investigated by employing a descriptor model transformation and a decomposition technique of the delay term matrix. The uncertainties under consideration are nonlinear perturbations and norm-bounded uncertainties, respectively. The proposed stability criteria are formulated in the form of a linear matrix inequality. Numerical examples are presented to indicate significant improvements over some existing results.

An improved stability criterion of networked control systems

The stability criterion of networked control systems with both the network-induced delays and data packet dropouts is investigated. A Lyapunov-Krasovskii functional candidate, which makes use of the information of the lower, upper bounds and the middle point of the time-varying network-induced delay interval simultaneously, is proposed and a tighter bounding for an integral term of the delay is estimated to drive a less conservative stability condition for networked control systems. No redundant matrix variable is introduced. Finally, two numerical examples are given to show the effectiveness of the proposed stability criterion.

Event-Triggered Control for Networked Takagi–Sugeno Fuzzy Systems

In this chapter, a discrete event-triggered communication scheme is used to save the limited network resource while preserving the desired performance and without resorting to extra hardware.

A Set-Membership Approach to Event-Triggered Filtering for General Nonlinear Systems Over Sensor Networks

This paper is concerned with the distributed set-membership filtering problem for a class of general discrete-time nonlinear systems under event-triggered communication protocols over sensor networks. To mitigate the communication burden, each intelligent sensing node broadcasts its measurement to the neighboring nodes only when a predetermined event-based media-access condition is satisfied. According to the interval mathematics theory, a recursive distributed set-membership scheme is designed to obtain an ellipsoid set containing the target states of interest via adequately fusing the measurements from neighboring nodes, where both the accurate estimate on Lagrange remainder and the event-based media-access condition are skillfully utilized to improve the filter performance. Furthermore, such a scheme is only dependent on neighbor information and local adjacency weights, thereby fulfilling the scalability requirement of sensor networks. In addition, an optimization algorithm is developed to minimize the trace of the estimated ellipsoid set, and the effect from the adopted event-triggered threshold is thoroughly discussed as well. Finally, a simulation example is utilized to illustrate the usefulness of the proposed distributed set-membership filtering scheme.

Adaptive learning-based recoil control for deepwater drilling riser systems

This paper deals with the adaptive learning based recoil suppression control problem of deepwater drilling riser systems subject to parametric perturbations, platform heave motion, and friction resistance force of drilling fluid discharge. First, a stochastic configuration network based approximator is presented to predict the friction resistance force of drilling fluid discharge. Then, model reference adaptive learning recoil controllers are developed for the drilling riser system, and the existence condition and supporting algorithm are provided. Simulation results show that: (i) the designed stochastic configuration network approximator is efficient to predict the friction resistance of drilling fluid discharge on the riser; (ii) the presented model reference adaptive learning recoil controllers are effective to restrain the recoil response of the riser; (iii) compared with the existing recoil controllers, which are all based on the exact dynamic recoil control models, the model reference adaptive learning recoil controllers proposed in this paper are no longer constrained by the accuracy of recoil model; (iv) the model reference adaptive learning recoil controllers are more robust than the existing ones to the unmodeled dynamics, systematic uncertainty, and parametric perturbations, and have better transient performance of system thereby guaranteeing the safety of the drilling riser systems effectively.

Synthesis of Triangular Metallodendrimers via Coordination-Driven Self-Assembly

A new family of 60° dendritic di-Pt(II) acceptor tectons have been successfully designed and synthesized, from which a series of novel "three-component" triangular metallodendrimers were prepared via [3 + 3] coordination-driven self-assembly. The structures of newly designed triangular metallodendrimers are characterized by multinuclear NMR (1H and 31P), 1H DOSY NMR, mass spectrometry (CSI-TOF-MS), and elemental analysis. The shape and size of all supramolecular dendritic triangles were investigated with PM6 semiempirical molecular orbital methods.

Recursive Secure Filtering Over Gilbert-Elliott Channels in Sensor Networks: The Distributed Case

This paper is concerned with the recursive secure filtering problem for a class of discrete-time systems subject to unreliable communication due to the security vulnerability of sensor networks. The unreliable communication, caused probably by denial-of-service cyber-attacks, is described by the well-known Gilbert-Elliott model. The addressed nonlinearities are applicable for some of the most investigated stochastic nonlinear models, including the well-known state-dependent multiplicative noises as special cases. The aim of this paper is to design a novel distributed filter that uses the information not only from the individual node itself but also from its neighboring nodes according to the given topology. In order to improve the security of designed filter, a χ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> detector is utilized to detect abnormal innovations. By means of the failure and recovery rates of the Gilbert-Elliott channels, sufficient conditions are established to ensure the existence of an upper bound on the estimation error covariance, and then the desired filter parameters are designed by minimizing the trace of such an upper bound. The asymptotic boundedness of the estimation error covariance is subsequently investigated. Finally, a simulation example on the target tracking problem is employed to verify the effectiveness and the security of the proposed filtering scheme.

Event-Based Set-Membership Leader-Following Consensus of Networked Multi-Agent Systems Subject to Limited Communication Resources and Unknown-But-Bounded Noise

This paper addresses the problem of leader-following consensus for networked multi-agent systems subject to limited communication resources and unknown-but-bounded process and measurement noise. First, a new distributed event-based communication mechanism on the basis of a time-varying threshold parameter is developed to schedule transmission of each sensor's measurement through a communication network so as to alleviate consecutive occupancy of communication resources. Second, a novel concept of set-membership leader-following consensus is put forward, through which the true states of all followers are guaranteed to always reside in a bounding ellipsoidal set of the leader's state. Third, in the case that full information of followers' states are not measurable, a distributed observer-based consensus protocol is presented to provide a set-membership estimation of each follower's state. Then, based on a recursive computation of confidence state estimation ellipsoids and leader state ellipsoid, a delicate convex optimization algorithm in terms of recursive linear matrix inequalities is proposed to design desired consensus protocol and event-based mechanism. Finally, an illustrative example is given to show the effectiveness and advantage of the developed approach.

One step prediction-based packet dropout compensation for networked control systems

This paper studies the problem of network induced delay and packet dropout compensation for continuous time networked control systems (NCSs). By proposing the one step prediction-based packet dropout compensation method, new model for NCSs with packet dropout and network-induced long delay is presented. Then, a packet dropout compensation threshold time based Lyapunov functional is proposed, and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller design method is presented. Even for NCSs without packet dropout compensation, the obtained result is still less conservative than the existing ones. This paper proves also that some existing results can be improved by using the convex analysis method. Numerical examples are given to illustrate the merits and effectiveness of the proposed methods.

A Cooperative Control Framework for a Collective Decision on Movement Behaviors of Particles

This paper deals with the problem of odor source localization by designing and analyzing a cooperative control framework (CCF) for the particle swarm optimization (PSO) algorithm. The CCF consists of three items: 1) a position coordination item; 2) a velocity coordination item; and 3) a movement direction coordination item. The position coordination item is used to coordinate relative positions between particles and to improve the exploration and exploitation capabilities of particles. The velocity coordination item enables the velocities of particles to reach consensus in order to realize orderly movement behaviors of particles. The movement direction coordination item guides particles to trace plumes and to locate odor sources. Stability of dynamic systems of particles with the proposed CCF is analyzed and the corresponding stability conditions are given such that the functions of three items in the CCF are realized. The orderly movement behaviors of particles under the CCF are also investigated based on benchmark functions. Finally, the effectiveness of the PSO algorithm with the proposed CCF is illustrated for the problem of odor source localization.